** Update (6/20/2017): Github now only allows access to 10 files per Gist, so you’ll need to clone the repository and open index.html in a browser to play with the d3 visualization.

I created a d3 visualization to explore commuter flows between US counties that were produced by my implementation of Simini et al. (2012)’s radiation model. You can play around with it on bl.ocks.org. The selected county appears red and you can toggle between commuter flows into and out of the county.

Radiation models, have been shown to improve the accuracy of describing many processes (in addition to commuting) that are affected by mobility and transport including migration, trade, and communication.

My radiation model used 2010 county level census data to generate inter-county commuter flows [radiation model source code].

Although there are limitations to the results it’s cool to see that this basic radiation model captures some long-distance movement patterns that other mobility predictors (like the gravity model) struggle with in the absence of data needed to fit parameters. For good examples check out Miami-Dade, Florida; Cook, Illinois; and Clark, Nevada.

As a future project I’d be interested in applying a radiation model to investigate the dynamics of human mobility and disease transmission across nations where accurate mobility data is not always available.

D3 Source Code: gist.github.com/renschler

Radiation Model Source Code: github.com/renschler/radiationmodel